Process engineering involves the design of a wide variety of processing plants and processes carried out therein. Such processes include, but are not limited to, chemical, petrochemical, refining, pharmaceutical, and polymer industries. In process engineering, the use of computer based models to develop and evaluate new processes, design and retrofit plants, and optimize the operation of existing plants is rapidly becoming a standard. At every stage of process design, development and operation, rigorous models generated by process simulation software systems can be used to make better engineering and business decisions.
In a process simulation software system, the performance of a process industry plant in which there is a continuous flow of materials and energy through a network of process units is simulated. The process unit can include equipment, such as distillation columns, retaining vessels, heating units, pumps, conduits, etc. Typically, the processing simulation software features computer models that allow process engineers to simulate the operation of various pieces of equipment used in a proposed or existing manufacturing process. The end results from the simulation software system provide a display of the simulated performance of the plant under various conditions and estimate of the capital and operating cost of the plant and its profitability.
Generally, simulation and optimization of a process plant model is carried out by one of two fundamentally different approaches. They are sequential modular simulation of the plant model, with an optimization algorithm ("optimization block") adjusting the optimization variables after each converged simulation of the complete plant model and, second, simultaneous solution of the entire plant model, which solves the plant model and optimizes its conditions at the same time. These approaches are discussed in U.S. Pat. No. 5,666,297, issued to Britt et al. on Sep. 9, 1997, the teachings of which are incorporated herein by reference.
However, there is a need for an improved method for simulating and optimizing a processing plant model in a digital processor.